Indexed by:期刊论文

Date of Publication:2013-08-15

Journal:JOURNAL OF CLEANER PRODUCTION

Included Journals:SCIE、EI、Scopus

Volume:53

Page Number:158-166

ISSN No.:0959-6526

Key Words:Artificial neural network; Ecological footprint; Spatial scales; Sustainability; Water resource

Abstract:A multi-scale assessment framework for evaluating water resource sustainability based on the ecological pressure index (EPI) is introduced. The study aims to correct the following flaws in the WEE: the difference between assessment and reality resulting from the fluidity of water resources; the lack of management and planning as a part of the dynamic tendency in the traditional water resource ecological footprint (WEF). The multi-scale EPI comprises the ratio of the WEF to water resource ecological carrying capacity (WECC) after comparing the traditional ecological footprint and the water footprint for correcting the former fault. Results show that the gap between the assessment and reality is more obvious from upstream to downstream. Such gap is demonstrated through the large differences in the EPI values of Panjin in 2002, with 13.87 in the city scale, 1.82 in the watershed scale involving the fluidity of the water resource among the cites, and 1.70 in the basin scale. The mean EPI values of the Liao-Hun and Taizi Watersheds are 136 and 1.17, respectively, indicating the imbalance of water resource supply and consumption between the watersheds. By forecasting the population, we determined that the time series prediction of EPI in the basin for the second flaws will exceed 1.33 in 2025, indicating that the water resource sustainability may be insufficient in the future. The proposed multi-scale assessment of WEF aims to evaluate the complex relationship between water resource supply and consumption in different spatial scales and time series. It also provides a more reasonable assessment result that can be used by managers and regulators. (C) 2013 Elsevier Ltd. All rights reserved.